Innovative Approaches to Optimization, Sustainability, and Safety in Transport and Logistics

1. Introduction: The Evolving Landscape of Mobility

Modern society is currently navigating a period of unprecedented transformation within the sectors of mobility and logistics, driven by three imperatives: the need for radical efficiency, the demand for environmental sustainability, and the rapid integration of Industry 4.0 technologies. As urban populations are projected to reach 68% of the global total by 2050, the pressure on existing infrastructure and environmental management systems has become a critical bottleneck for economic growth and quality of life. Traditional methods of managing logistics chains and transport networks are reaching their operational limits due to the increasing complexity of urban environments and rising freight volumes. Consequently, sustainability is no longer a peripheral concern but a core requirement for modern engineering and policy-making. The transport sector remains one of the most significant contributors to emissions and external costs, ranging from traffic congestion and air pollution to climate change. This Special Issue presents a curated collection of six scientific papers that address these challenges through a multi-disciplinary lens, filling critical knowledge gaps using advanced mathematical modeling, comparative methodological analysis, and the deployment of autonomous systems.

2. Strategic Evaluation and Quality Management in Passenger Transport

A fundamental prerequisite for a sustainable transport future is the objective evaluation of infrastructure projects and the quality of services provided to the public. Vladimír Konečný et al. address the former by identifying significant disproportions in the cost–benefit analysis (CBA) methodologies used across Central European countries (Slovakia, Czech Republic, Hungary, and Austria) regarding greenhouse gas (GHG) emissions. Their research highlights a critical methodological gap: while international standards have moved toward a Well-to-Wheel (WtW) approach, some national methodologies still overlook the indirect emissions (Well-to-Tank) associated with fuel production and distribution. A case study reveals that the calculated climate change costs for a model transport route in Slovakia are up to nine times higher than those calculated under the Hungarian methodology, emphasizing the urgent need for harmonized and updated emission factors to ensure realistic investment decisions.

Parallel to economic evaluation is the subjective perception of service quality. Milan Živković and Borna Abramović provide a comprehensive review of quality of service (QoS) criteria within Integrated Passenger Transport Systems (IPTS). By revising the European Standard EN 13816 [1], the authors argue that traditional mode-specific evaluations are insufficient for complex integrated networks. They propose a shift toward network-based criteria, where integrated travel information and total travel time (including transfers) become the primary indicators of service excellence. Their findings suggest that improving these specific QoS dimensions is the most effective way to encourage a modal shift from private vehicles to public transport, thereby reducing the environmental footprint of urban mobility.

3. Mathematical Rigor in Network Reliability and Resilience

The operational efficiency of transport hubs and lines often depends on how they manage stochastic disturbances. Abate Sewagegn and Michal Dorda contribute to this field by modeling railway marshaling yard processes using a finite-capacity queuing model (M/HypoK/1/m) under failure conditions. In a novel approach, they treat secondary shunting operations—often viewed as a routine part of yard work—as system “failures” because they interrupt the primary function of train classification. Their research proves that the hypo-exponential distribution is a robust tool for approximating complex gamma distributions, providing railway engineers with a mathematically trackable framework for capacity planning and failure mitigation in high-pressure freight environments.

On the level of urban transit, Pavle Pitka et al. tackle the phenomenon of “bus bunching” through planning-level optimization. Unlike real-time interventions, their model focuses on increasing system robustness by evaluating the splitting of long diametrical lines into shorter radial ones. Using the Percentage Regularity Deviation Mean (PRDM) index, their study demonstrates that line splitting effectively interrupts the propagation of delays along a route. Their sensitivity analysis reveals that this intervention is most beneficial during peak hours for lines with short headways and high demand, particularly when primary disturbances exceed two minutes. This research provides a vital tool for transport planners to balance the trade-off between increased transfer requirements and improved headway regularity.

4. Operational Innovation Through Automation and Routing

The final pillar of this issue focuses on practical implementations in logistics through routing optimization and robotics. Jaroslav Mašek et al. [2] demonstrate the power of the Clark-Wright Savings Algorithm in optimizing municipal waste collection in the Žilina region. By restructuring the logistics chain for over 100 municipalities, they achieved a reduction in the number of routes from 65 to 45, saving 2449 km per week. This optimization not only results in significant financial savings—approximately EUR 2205 per week in fuel costs—but also contributes to a massive reduction in the urban footprint and annual fuel consumption by over 1469 L.

The theme of efficiency is further explored by Iveta Kubasáková et al. [3], who compare the deployment of Autonomous Mobile Robots (AMRs) against human labor in industrial logistics. Their analysis of a manufacturing plant’s supply process shows that while a human-operated “logistics train” is subject to fatigue and error, an AMR fleet provides 100% uptime and higher safety. By replacing eight human workers (across four shifts) with four AMR units, the company can achieve a return on investment (ROI) in approximately 1.08 years (395 days). Beyond simple cost-cutting, the study highlights that AMRs can reduce internal shipping times by 30% to 50%, representing a transformative step toward fully automated “Smart Factories”.

5. Conclusions and Future Research Trajectories

The collective findings published in this Special Issue underscore that the future of transport and logistics lies in the synergy between mathematical precision and technological innovation [Turn 4]. These studies collectively address major knowledge gaps, such as the neglect of indirect emissions in economic appraisals, the lack of network-integrated quality criteria, and the need for more flexible stochastic modeling in infrastructure hubs.

Moving forward, potential research directions should include:

• Dynamic Real-Time Optimization: Integrating IoT sensors for real-time tracking of container fill levels or traffic conditions to move beyond static routing.
• Lifecycle and Energy Analysis: Exploring the long-term impact of battery life cycles in autonomous systems and the integration of green energy sources for electric bus fleets.
• Hybrid Management Models: Developing systems that combine planning-level robustness (like line splitting) with real-time adaptive control strategies.
• Social Impact Assessments: Investigating the socio-economic transitions required as automation (AMRs) increasingly replaces manual labor in the logistics sector.

We trust that these contributions will stimulate further academic inquiry and provide practical guidance for industry professionals striving toward a more resilient, efficient, and sustainable global transport network.